Neural networks, i.e. neural calculation, is used for the analysis of various processes. One known neural network model is SOM (self oriented map). Such algorithms are used to form a database from the vectors of the output variables, with the aid of various process situations. Measurement vectors, which are compared with the vectors in the database, are calculated from the measurement values obtained in the process situation. If these deviate by certain criteria from all the vectors, an attempt is made to analyse what difference or differences in the output variables caused the difference in question.
Often when applying the neural network technique, a large number of process variables are included, but the results are not satisfactory. Apparently, some of the output variables have been particularly unstable, in which case they have upset the study, and have not properly represented the process situation.
Patent publications U.S. Pat. Nos. 4,818,348; 5,830,343; 5,393,399; 5,654,497; and EP 692711 disclose some liquid analysers that use polarographic sensors. In the first publication referred to, the liquid is vaporized and the vapour is led through parallel sensors. Finnish patent application 892351 also discloses a disposal electrochemical sensor, which is intended for medical use. The generally known sensors have a narrow area of application and they are usually only able to measure a few predefined substances and their contents in a liquid. A sensor according to publication U.S. Pat. No. 5,830,343 will not remain in operating condition for long, because even individual fibres can cause a short-circuit between the electrodes of the tiny sensor.